For dot product I can convince myself this is a math definition thing and accept the conjugation. But for "vecmat" why the complex conjugate of the vector? Are we assuming that 1D things are always columns. I am also a bit lost on the difference of dot, vdot and vecdot. Also if __matmul__ and np.matmul give different results, I think you will enjoy many fun tickets. Personally I would agree with them no matter what the reasoning was at the time of divergence. On Tue, Jan 23, 2024 at 11:17 PM Marten van Kerkwijk <mhvk@astro.utoronto.ca> wrote:
Hi All,
I have a PR [1] that adds `np.matvec` and `np.vecmat` gufuncs for matrix-vector and vector-matrix calculations, to add to plain matrix-matrix multiplication with `np.matmul` and the inner vector product with `np.vecdot`. They call BLAS where possible for speed. I'd like to hear whether these are good additions.
I also note that for complex numbers, `vecmat` is defined as `x†A`, i.e., the complex conjugate of the vector is taken. This seems to be the standard and is what we used for `vecdot` too (`x†x`). However, it is *not* what `matmul` does for vector-matrix or indeed vector-vector products (remember that those are possible only if the vector is one-dimensional, i.e., not with a stack of vectors). I think this is a bug in matmul, which I'm happy to fix. But I'm posting here in part to get feedback on that.
Thanks!
Marten
[1] https://github.com/numpy/numpy/pull/25675
p.s. Separately, with these functions available, in principle these could be used in `__matmul__` (and thus for `@`) and the specializations in `np.matmul` removed. But that can be a separate PR (if it is wanted at all). _______________________________________________ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an email to numpy-discussion-leave@python.org https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ Member address: ilhanpolat@gmail.com